Overview

Dataset statistics

Number of variables14
Number of observations52704
Missing cells7862
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 MiB
Average record size in memory112.0 B

Variable types

DateTime1
Numeric13

Alerts

Power (kW) is highly overall correlated with Rear bearing temperature (°C) and 6 other fieldsHigh correlation
Wind direction (°) is highly overall correlated with Nacelle position (°)High correlation
Nacelle position (°) is highly overall correlated with Wind direction (°)High correlation
Rear bearing temperature (°C) is highly overall correlated with Power (kW) and 4 other fieldsHigh correlation
Rotor speed (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Generator RPM (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Front bearing temperature (°C) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration X (mm/ss) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
Wind speed (m/s) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration y (mm/ss) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
blade_angle has 722 (1.4%) missing valuesMissing
Rear bearing temperature (°C) has 722 (1.4%) missing valuesMissing
Nacelle ambient temperature (°C) has 722 (1.4%) missing valuesMissing
Front bearing temperature (°C) has 722 (1.4%) missing valuesMissing
Tower Acceleration X (mm/ss) has 722 (1.4%) missing valuesMissing
Tower Acceleration y (mm/ss) has 722 (1.4%) missing valuesMissing
Metal particle count counter has 722 (1.4%) missing valuesMissing
# Date and time has unique valuesUnique
blade_angle has 22605 (42.9%) zerosZeros
Rotor speed (RPM) has 1403 (2.7%) zerosZeros

Reproduction

Analysis started2023-07-08 11:58:10.020046
Analysis finished2023-07-08 11:58:27.254442
Duration17.23 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Distinct52704
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size411.9 KiB
Minimum2020-01-01 00:00:00
Maximum2020-12-31 23:50:00
2023-07-08T17:28:27.305475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:27.406406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Power (kW)
Real number (ℝ)

Distinct52204
Distinct (%)99.9%
Missing468
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean716.46721
Minimum-16.487485
Maximum2078.5288
Zeros3
Zeros (%)< 0.1%
Negative5332
Negative (%)10.1%
Memory size411.9 KiB
2023-07-08T17:28:27.515229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-16.487485
5-th percentile-1.1112805
Q1133.56816
median483.31285
Q31194.3082
95-th percentile2030.5544
Maximum2078.5288
Range2095.0163
Interquartile range (IQR)1060.74

Descriptive statistics

Standard deviation680.55277
Coefficient of variation (CV)0.94987288
Kurtosis-0.80041516
Mean716.46721
Median Absolute Deviation (MAD)418.5269
Skewness0.75437785
Sum37425381
Variance463152.07
MonotonicityNot monotonic
2023-07-08T17:28:27.617804image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
< 0.1%
-0.8680045247 2
 
< 0.1%
-0.9016150266 2
 
< 0.1%
-0.1339085028 2
 
< 0.1%
-1.466058037 2
 
< 0.1%
-0.877074033 2
 
< 0.1%
66.25 2
 
< 0.1%
-0.8808085293 2
 
< 0.1%
-0.4353360105 2
 
< 0.1%
-1.360425004 2
 
< 0.1%
Other values (52194) 52215
99.1%
(Missing) 468
 
0.9%
ValueCountFrequency (%)
-16.48748454 1
< 0.1%
-16.16778612 1
< 0.1%
-15.84177451 1
< 0.1%
-15.41067309 1
< 0.1%
-14.51299555 1
< 0.1%
-14.14635161 1
< 0.1%
-13.87526748 1
< 0.1%
-13.48619313 1
< 0.1%
-13.39871354 1
< 0.1%
-13.34724381 1
< 0.1%
ValueCountFrequency (%)
2078.528772 1
< 0.1%
2077.179653 1
< 0.1%
2076.502399 1
< 0.1%
2074.126593 1
< 0.1%
2073.92702 1
< 0.1%
2073.652277 1
< 0.1%
2072.727686 1
< 0.1%
2072.654041 1
< 0.1%
2072.573456 1
< 0.1%
2072.071393 1
< 0.1%

Wind direction (°)
Real number (ℝ)

Distinct52235
Distinct (%)> 99.9%
Missing468
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean197.94054
Minimum0.014923042
Maximum359.96236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:27.718684image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.014923042
5-th percentile32.589519
Q1142.18551
median217.52935
Q3258.12409
95-th percentile332.37407
Maximum359.96236
Range359.94743
Interquartile range (IQR)115.93857

Descriptive statistics

Standard deviation91.136738
Coefficient of variation (CV)0.46042483
Kurtosis-0.64490773
Mean197.94054
Median Absolute Deviation (MAD)49.616412
Skewness-0.53906997
Sum10339622
Variance8305.9051
MonotonicityNot monotonic
2023-07-08T17:28:27.824157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94.70999908 2
 
< 0.1%
116.8394619 1
 
< 0.1%
188.6904369 1
 
< 0.1%
25.29755689 1
 
< 0.1%
292.2764537 1
 
< 0.1%
267.4767873 1
 
< 0.1%
176.798142 1
 
< 0.1%
116.9903754 1
 
< 0.1%
62.08090401 1
 
< 0.1%
337.2157063 1
 
< 0.1%
Other values (52225) 52225
99.1%
(Missing) 468
 
0.9%
ValueCountFrequency (%)
0.01492304184 1
< 0.1%
0.04839388999 1
< 0.1%
0.08445749258 1
< 0.1%
0.1235740284 1
< 0.1%
0.1294222759 1
< 0.1%
0.1557199658 1
< 0.1%
0.1961232467 1
< 0.1%
0.2029436894 1
< 0.1%
0.2069624434 1
< 0.1%
0.2235601553 1
< 0.1%
ValueCountFrequency (%)
359.9623575 1
< 0.1%
359.9491562 1
< 0.1%
359.9456596 1
< 0.1%
359.9249327 1
< 0.1%
359.9157439 1
< 0.1%
359.9118556 1
< 0.1%
359.896517 1
< 0.1%
359.8904576 1
< 0.1%
359.8788605 1
< 0.1%
359.8729557 1
< 0.1%

Nacelle position (°)
Real number (ℝ)

Distinct12576
Distinct (%)24.1%
Missing468
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean197.87621
Minimum0.029887829
Maximum359.98649
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:27.935863image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.029887829
5-th percentile31.739755
Q1144.34042
median217.87778
Q3258.48819
95-th percentile332.02451
Maximum359.98649
Range359.9566
Interquartile range (IQR)114.14777

Descriptive statistics

Standard deviation91.298291
Coefficient of variation (CV)0.46139095
Kurtosis-0.64768269
Mean197.87621
Median Absolute Deviation (MAD)49.390411
Skewness-0.545575
Sum10336262
Variance8335.378
MonotonicityNot monotonic
2023-07-08T17:28:28.040539image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213.4880371 285
 
0.5%
247.5120239 238
 
0.5%
236.5368958 230
 
0.4%
247.5125427 228
 
0.4%
214.585083 215
 
0.4%
41.17092514 202
 
0.4%
246.414978 202
 
0.4%
259.5857544 198
 
0.4%
248.6095886 197
 
0.4%
300.1956482 194
 
0.4%
Other values (12566) 50047
95.0%
(Missing) 468
 
0.9%
ValueCountFrequency (%)
0.02988782898 1
 
< 0.1%
0.0882467468 1
 
< 0.1%
0.360822317 1
 
< 0.1%
0.5611712933 13
< 0.1%
0.5611877441 9
 
< 0.1%
0.5611884594 15
< 0.1%
0.5617052913 30
0.1%
0.5617064834 29
0.1%
0.5891515433 1
 
< 0.1%
0.7387967054 1
 
< 0.1%
ValueCountFrequency (%)
359.9864855 1
 
< 0.1%
359.9442048 1
 
< 0.1%
359.9372254 1
 
< 0.1%
359.8529598 1
 
< 0.1%
359.695399 1
 
< 0.1%
359.6844202 1
 
< 0.1%
359.6332999 1
 
< 0.1%
359.5247983 1
 
< 0.1%
359.4641418 4
 
< 0.1%
359.463623 55
0.1%

blade_angle
Real number (ℝ)

MISSING  ZEROS 

Distinct21574
Distinct (%)41.5%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean6.3828256
Minimum0
Maximum92.730003
Zeros22605
Zeros (%)42.9%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:28.147813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.062999754
Q31.5456736
95-th percentile44.996667
Maximum92.730003
Range92.730003
Interquartile range (IQR)1.5456736

Descriptive statistics

Standard deviation16.77893
Coefficient of variation (CV)2.628762
Kurtosis11.721465
Mean6.3828256
Median Absolute Deviation (MAD)0.062999754
Skewness3.3664635
Sum331792.04
Variance281.53248
MonotonicityNot monotonic
2023-07-08T17:28:28.353060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22605
42.9%
44.99666723 1599
 
3.0%
44.99333445 1555
 
3.0%
89.99333191 622
 
1.2%
0.02466666698 321
 
0.6%
1.49666667 178
 
0.3%
0.02483333349 171
 
0.3%
92.24333191 161
 
0.3%
1.49333334 135
 
0.3%
0.04933333397 99
 
0.2%
Other values (21564) 24536
46.6%
(Missing) 722
 
1.4%
ValueCountFrequency (%)
0 22605
42.9%
0.0001666666622 9
 
< 0.1%
0.0001666666629 17
 
< 0.1%
0.0001754385926 2
 
< 0.1%
0.000185185181 2
 
< 0.1%
0.000196078427 2
 
< 0.1%
0.0002083333287 2
 
< 0.1%
0.0003333333201 2
 
< 0.1%
0.0003333333244 8
 
< 0.1%
0.0003333333259 16
 
< 0.1%
ValueCountFrequency (%)
92.73000336 2
 
< 0.1%
92.71666718 1
 
< 0.1%
92.70333354 1
 
< 0.1%
92.52838402 1
 
< 0.1%
92.49666595 32
0.1%
92.42999776 9
 
< 0.1%
92.36249797 1
 
< 0.1%
92.32476153 1
 
< 0.1%
92.31999969 1
 
< 0.1%
92.28933309 1
 
< 0.1%

Rear bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38403
Distinct (%)73.9%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean64.332109
Minimum9.8999996
Maximum76.752499
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:28.445127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.8999996
5-th percentile42.742875
Q164.139605
median67.4425
Q369.264926
95-th percentile71.3225
Maximum76.752499
Range66.8525
Interquartile range (IQR)5.1253203

Descriptive statistics

Standard deviation9.5553443
Coefficient of variation (CV)0.1485315
Kurtosis9.4100117
Mean64.332109
Median Absolute Deviation (MAD)2.1674997
Skewness-2.8648709
Sum3344111.7
Variance91.304604
MonotonicityNot monotonic
2023-07-08T17:28:28.540338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67.09999847 26
 
< 0.1%
69.5375 11
 
< 0.1%
68.18250008 10
 
< 0.1%
68.75 10
 
< 0.1%
67.7 10
 
< 0.1%
69.5 9
 
< 0.1%
68.675 9
 
< 0.1%
67.175 9
 
< 0.1%
69.42249985 9
 
< 0.1%
68.0125 9
 
< 0.1%
Other values (38393) 51870
98.4%
(Missing) 722
 
1.4%
ValueCountFrequency (%)
9.899999619 1
< 0.1%
9.912499666 1
< 0.1%
9.919999695 1
< 0.1%
9.937499714 1
< 0.1%
9.937499762 2
< 0.1%
9.964999771 1
< 0.1%
9.972499895 1
< 0.1%
9.97368411 1
< 0.1%
9.981578877 1
< 0.1%
10.03999996 2
< 0.1%
ValueCountFrequency (%)
76.75249939 1
< 0.1%
76.5125 1
< 0.1%
75.84500122 1
< 0.1%
75.75999985 1
< 0.1%
75.74333191 1
< 0.1%
75.69499664 1
< 0.1%
75.61388652 1
< 0.1%
75.60749779 1
< 0.1%
75.58749847 1
< 0.1%
75.58749809 1
< 0.1%

Rotor speed (RPM)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50607
Distinct (%)96.9%
Missing468
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean10.765336
Minimum0
Maximum15.343201
Zeros1403
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:28.642312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.48799421
Q18.3587463
median11.428051
Q314.63761
95-th percentile15.167726
Maximum15.343201
Range15.343201
Interquartile range (IQR)6.2788637

Descriptive statistics

Standard deviation4.2340349
Coefficient of variation (CV)0.39330261
Kurtosis0.64003277
Mean10.765336
Median Absolute Deviation (MAD)3.1251165
Skewness-1.089045
Sum562338.11
Variance17.927051
MonotonicityNot monotonic
2023-07-08T17:28:28.738328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1403
 
2.7%
8.140000343 48
 
0.1%
0.01050000242 19
 
< 0.1%
15.15999985 17
 
< 0.1%
0.0110000018 16
 
< 0.1%
0.01150000188 14
 
< 0.1%
8.149999619 8
 
< 0.1%
15.14999962 8
 
< 0.1%
0.01200000197 8
 
< 0.1%
0.01250000205 7
 
< 0.1%
Other values (50597) 50688
96.2%
(Missing) 468
 
0.9%
ValueCountFrequency (%)
0 1403
2.7%
0.0001870000415 1
 
< 0.1%
0.0002160000295 1
 
< 0.1%
0.001617000438 1
 
< 0.1%
0.00180000026 1
 
< 0.1%
0.004818500835 1
 
< 0.1%
0.006289501442 1
 
< 0.1%
0.007951501524 1
 
< 0.1%
0.009366002167 1
 
< 0.1%
0.00957500143 1
 
< 0.1%
ValueCountFrequency (%)
15.34320107 1
< 0.1%
15.34083854 1
< 0.1%
15.30233999 1
< 0.1%
15.29815578 1
< 0.1%
15.2955671 1
< 0.1%
15.29039964 1
< 0.1%
15.28881669 1
< 0.1%
15.28221045 1
< 0.1%
15.28205404 1
< 0.1%
15.28150257 1
< 0.1%

Generator RPM (RPM)
Real number (ℝ)

Distinct52192
Distinct (%)99.9%
Missing468
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean1276.8912
Minimum0
Maximum1819.4091
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:28.841024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile60.306365
Q1993.24965
median1355.6734
Q31734.0876
95-th percentile1796.7745
Maximum1819.4091
Range1819.4091
Interquartile range (IQR)740.83796

Descriptive statistics

Standard deviation500.53143
Coefficient of variation (CV)0.39199223
Kurtosis0.65359835
Mean1276.8912
Median Absolute Deviation (MAD)368.88057
Skewness-1.0946102
Sum66699688
Variance250531.71
MonotonicityNot monotonic
2023-07-08T17:28:28.935976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5
 
< 0.1%
970.039978 4
 
< 0.1%
969.960022 3
 
< 0.1%
970.0900269 3
 
< 0.1%
969.8900146 3
 
< 0.1%
1795.916342 2
 
< 0.1%
968.0939484 2
 
< 0.1%
970.1799927 2
 
< 0.1%
967.9124794 2
 
< 0.1%
970 2
 
< 0.1%
Other values (52182) 52208
99.1%
(Missing) 468
 
0.9%
ValueCountFrequency (%)
0 5
< 0.1%
0.03999999911 1
 
< 0.1%
0.4834296824 1
 
< 0.1%
0.4992865124 1
 
< 0.1%
0.5205166787 1
 
< 0.1%
0.5238284008 1
 
< 0.1%
0.530410309 1
 
< 0.1%
0.5324476808 1
 
< 0.1%
0.5422512721 1
 
< 0.1%
0.5434771563 1
 
< 0.1%
ValueCountFrequency (%)
1819.409071 1
< 0.1%
1816.75593 1
< 0.1%
1811.135118 1
< 0.1%
1810.909864 1
< 0.1%
1810.904114 1
< 0.1%
1810.360119 1
< 0.1%
1810.060301 1
< 0.1%
1809.779617 1
< 0.1%
1809.630781 1
< 0.1%
1809.345606 1
< 0.1%
Distinct38718
Distinct (%)74.5%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean11.911598
Minimum-1.6675
Maximum35.48
Zeros0
Zeros (%)0.0%
Negative149
Negative (%)0.3%
Memory size411.9 KiB
2023-07-08T17:28:29.038948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-1.6675
5-th percentile3.915
Q17.6199999
median11.29
Q315.715
95-th percentile22.035
Maximum35.48
Range37.1475
Interquartile range (IQR)8.095

Descriptive statistics

Standard deviation5.6467856
Coefficient of variation (CV)0.47405777
Kurtosis0.10526729
Mean11.911598
Median Absolute Deviation (MAD)4.0549998
Skewness0.53309051
Sum619188.69
Variance31.886187
MonotonicityNot monotonic
2023-07-08T17:28:29.132747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.5 62
 
0.1%
10.60000038 50
 
0.1%
10.69999981 49
 
0.1%
6 46
 
0.1%
7 44
 
0.1%
8.899999619 43
 
0.1%
9.5 43
 
0.1%
10.19999981 42
 
0.1%
10.80000019 41
 
0.1%
7.900000095 41
 
0.1%
Other values (38708) 51521
97.8%
(Missing) 722
 
1.4%
ValueCountFrequency (%)
-1.667500037 1
 
< 0.1%
-1.627777808 1
 
< 0.1%
-1.61250003 1
 
< 0.1%
-1.602500027 1
 
< 0.1%
-1.600000024 3
< 0.1%
-1.597368441 1
 
< 0.1%
-1.590000021 1
 
< 0.1%
-1.575000012 1
 
< 0.1%
-1.560000014 1
 
< 0.1%
-1.550000028 1
 
< 0.1%
ValueCountFrequency (%)
35.48000031 1
< 0.1%
35.28235312 1
< 0.1%
35.24473712 1
< 0.1%
35.24000015 1
< 0.1%
35.13235317 1
< 0.1%
35.11750011 1
< 0.1%
34.88421109 1
< 0.1%
34.83157971 1
< 0.1%
34.66052648 1
< 0.1%
34.63999977 1
< 0.1%

Front bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39184
Distinct (%)75.4%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean66.409001
Minimum9.5605265
Maximum78.752501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:29.235452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.5605265
5-th percentile42.453
Q163.735625
median71.265395
Q373.007186
95-th percentile74.718421
Maximum78.752501
Range69.191974
Interquartile range (IQR)9.2715613

Descriptive statistics

Standard deviation10.990956
Coefficient of variation (CV)0.165504
Kurtosis5.5715386
Mean66.409001
Median Absolute Deviation (MAD)2.5171042
Skewness-2.2303797
Sum3452072.7
Variance120.80111
MonotonicityNot monotonic
2023-07-08T17:28:29.330619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.89999962 22
 
< 0.1%
72.375 11
 
< 0.1%
73.78249931 10
 
< 0.1%
71.58499985 10
 
< 0.1%
72.91999969 10
 
< 0.1%
72.71249962 10
 
< 0.1%
10 10
 
< 0.1%
73.49000015 9
 
< 0.1%
72.99999962 9
 
< 0.1%
73.25 9
 
< 0.1%
Other values (39174) 51872
98.4%
(Missing) 722
 
1.4%
ValueCountFrequency (%)
9.560526547 1
 
< 0.1%
9.577500248 1
 
< 0.1%
9.600000381 5
< 0.1%
9.627500153 1
 
< 0.1%
9.637500143 1
 
< 0.1%
9.662499952 1
 
< 0.1%
9.662500048 1
 
< 0.1%
9.669999981 1
 
< 0.1%
9.692499828 1
 
< 0.1%
9.699999809 7
< 0.1%
ValueCountFrequency (%)
78.75250092 1
< 0.1%
78.66500015 1
< 0.1%
78.29500237 1
< 0.1%
78.26500092 1
< 0.1%
78.2200002 1
< 0.1%
78.1599987 1
< 0.1%
78.08055539 1
< 0.1%
78.07000008 1
< 0.1%
78.04749985 1
< 0.1%
78.04500046 1
< 0.1%

Tower Acceleration X (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51979
Distinct (%)> 99.9%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean54.783585
Minimum3.2189207
Maximum252.05823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:29.430326image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3.2189207
5-th percentile5.229377
Q136.383752
median53.422227
Q371.88244
95-th percentile104.91274
Maximum252.05823
Range248.83931
Interquartile range (IQR)35.498689

Descriptive statistics

Standard deviation29.300691
Coefficient of variation (CV)0.53484435
Kurtosis0.9187487
Mean54.783585
Median Absolute Deviation (MAD)17.723042
Skewness0.53165008
Sum2847760.3
Variance858.53049
MonotonicityNot monotonic
2023-07-08T17:28:29.529917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45.26737003 2
 
< 0.1%
92.76933222 2
 
< 0.1%
4.725139642 2
 
< 0.1%
103.1257966 1
 
< 0.1%
4.938505489 1
 
< 0.1%
4.339167331 1
 
< 0.1%
4.519380099 1
 
< 0.1%
4.846164852 1
 
< 0.1%
4.643520689 1
 
< 0.1%
5.005810398 1
 
< 0.1%
Other values (51969) 51969
98.6%
(Missing) 722
 
1.4%
ValueCountFrequency (%)
3.218920708 1
< 0.1%
3.278675318 1
< 0.1%
3.317099214 1
< 0.1%
3.321688287 1
< 0.1%
3.327484125 1
< 0.1%
3.351915742 1
< 0.1%
3.396557194 1
< 0.1%
3.493809569 1
< 0.1%
3.546519387 1
< 0.1%
3.550701463 1
< 0.1%
ValueCountFrequency (%)
252.0582287 1
< 0.1%
233.6856979 1
< 0.1%
229.4219206 1
< 0.1%
226.1190712 1
< 0.1%
223.866827 1
< 0.1%
221.3711075 1
< 0.1%
218.5714451 1
< 0.1%
214.7583927 1
< 0.1%
213.9458241 1
< 0.1%
213.831087 1
< 0.1%

Wind speed (m/s)
Real number (ℝ)

Distinct52133
Distinct (%)99.8%
Missing468
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean6.5244023
Minimum0.25831909
Maximum22.419562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:29.629830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.25831909
5-th percentile2.2481345
Q14.3134927
median6.225888
Q38.3116493
95-th percentile11.919605
Maximum22.419562
Range22.161243
Interquartile range (IQR)3.9981566

Descriptive statistics

Standard deviation3.0110097
Coefficient of variation (CV)0.4614997
Kurtosis0.58515039
Mean6.5244023
Median Absolute Deviation (MAD)1.9843215
Skewness0.67613612
Sum340808.68
Variance9.0661794
MonotonicityNot monotonic
2023-07-08T17:28:29.726350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.789999962 5
 
< 0.1%
3.160000086 4
 
< 0.1%
2.74000001 3
 
< 0.1%
4.210000038 3
 
< 0.1%
2.660000086 3
 
< 0.1%
2.710000038 3
 
< 0.1%
3.130000114 3
 
< 0.1%
5.708495378 2
 
< 0.1%
2.869999886 2
 
< 0.1%
2.079999924 2
 
< 0.1%
Other values (52123) 52206
99.1%
(Missing) 468
 
0.9%
ValueCountFrequency (%)
0.2583190901 1
< 0.1%
0.2659313828 1
< 0.1%
0.2990063034 1
< 0.1%
0.3096751668 1
< 0.1%
0.3125527125 1
< 0.1%
0.3162564248 1
< 0.1%
0.316368977 1
< 0.1%
0.3296815138 1
< 0.1%
0.35656882 1
< 0.1%
0.3613688039 1
< 0.1%
ValueCountFrequency (%)
22.41956224 1
< 0.1%
21.83115921 1
< 0.1%
21.77834992 1
< 0.1%
21.7256063 1
< 0.1%
21.65618397 1
< 0.1%
21.62340162 1
< 0.1%
21.53602519 1
< 0.1%
21.50651259 1
< 0.1%
21.46336012 1
< 0.1%
21.44604383 1
< 0.1%

Tower Acceleration y (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51980
Distinct (%)> 99.9%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean29.769359
Minimum3.2377861
Maximum243.02611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:29.820499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3.2377861
5-th percentile5.2910278
Q117.878002
median26.528803
Q338.12217
95-th percentile62.249723
Maximum243.02611
Range239.78832
Interquartile range (IQR)20.244168

Descriptive statistics

Standard deviation18.325773
Coefficient of variation (CV)0.61559178
Kurtosis7.6419943
Mean29.769359
Median Absolute Deviation (MAD)9.829001
Skewness1.8014802
Sum1547470.8
Variance335.83394
MonotonicityNot monotonic
2023-07-08T17:28:29.922046image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.28589354 2
 
< 0.1%
38.70155764 2
 
< 0.1%
4.907157673 1
 
< 0.1%
4.92992315 1
 
< 0.1%
4.685312402 1
 
< 0.1%
4.540654719 1
 
< 0.1%
3.77995311 1
 
< 0.1%
4.211181471 1
 
< 0.1%
5.300654727 1
 
< 0.1%
7.15883472 1
 
< 0.1%
Other values (51970) 51970
98.6%
(Missing) 722
 
1.4%
ValueCountFrequency (%)
3.237786067 1
< 0.1%
3.341573668 1
< 0.1%
3.487803119 1
< 0.1%
3.489523869 1
< 0.1%
3.509723413 1
< 0.1%
3.521330741 1
< 0.1%
3.530324602 1
< 0.1%
3.532317454 1
< 0.1%
3.544485255 1
< 0.1%
3.566362816 1
< 0.1%
ValueCountFrequency (%)
243.0261078 1
< 0.1%
232.6705378 1
< 0.1%
222.9757862 1
< 0.1%
215.8486031 1
< 0.1%
212.6895702 1
< 0.1%
209.0473637 1
< 0.1%
206.6283544 1
< 0.1%
206.5478495 1
< 0.1%
203.9238604 1
< 0.1%
203.426317 1
< 0.1%
Distinct20
Distinct (%)< 0.1%
Missing722
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean697.14078
Minimum687
Maximum708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:30.011317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum687
5-th percentile687
Q1693
median698
Q3702
95-th percentile706
Maximum708
Range21
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.6388077
Coefficient of variation (CV)0.0080884777
Kurtosis-1.0464809
Mean697.14078
Median Absolute Deviation (MAD)5
Skewness-0.22398047
Sum36238772
Variance31.796152
MonotonicityIncreasing
2023-07-08T17:28:30.082143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
698 9030
17.1%
693 5400
10.2%
702 5328
10.1%
691 4520
8.6%
699 3984
7.6%
704 3917
7.4%
688 3000
 
5.7%
687 2689
 
5.1%
696 2196
 
4.2%
703 2167
 
4.1%
Other values (10) 9751
18.5%
ValueCountFrequency (%)
687 2689
 
5.1%
688 3000
 
5.7%
689 1
 
< 0.1%
690 2075
 
3.9%
691 4520
8.6%
693 5400
10.2%
694 727
 
1.4%
695 208
 
0.4%
696 2196
 
4.2%
698 9030
17.1%
ValueCountFrequency (%)
708 308
 
0.6%
707 441
 
0.8%
706 2087
 
4.0%
705 976
 
1.9%
704 3917
7.4%
703 2167
4.1%
702 5328
10.1%
701 2022
 
3.8%
700 906
 
1.7%
699 3984
7.6%

Interactions

2023-07-08T17:28:25.398980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:11.593753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.681424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.911079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.052380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.124778image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.270615image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.538205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.682873image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.829720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.091784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.200931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.284711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.477715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:11.671277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.763680image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.994179image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.127588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.207870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.353668image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.618555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.765931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.912987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.172133image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.278708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.363187image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.562999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:11.757100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.852990image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.083843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.214322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.299016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.445092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.710755image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.856875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.004811image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.259108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.364132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.451376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.649600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:11.846436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.943690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.174392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.298701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.390397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.539256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.801290image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.948347image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.094662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.348182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.450029image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.543037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.852255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:11.924833image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.025838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.258713image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.373327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.471562image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.620077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.884846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.030786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.177926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.427109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.528917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.623228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.940308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.012754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.118602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.352696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.460472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.562611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.829122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.976682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.122126image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.268909image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.518262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.615689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.714738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.031745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.103298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.211341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.444652image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.547328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.657934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.921993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.071684image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.217002image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.363941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.609345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.706018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.805110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.119440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.189343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.303732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.537706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.633906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.749376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.013675image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.159905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.306975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.455006image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.698599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.791224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.895254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.208103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.275866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.394461image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.627677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.720955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.840514image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.105438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.253424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.398322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.662739image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.787710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.878893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.985575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.294872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.363670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.487779image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.720085image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.810592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.931697image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.198749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.344901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.489698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.752803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.877691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.966442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.076260image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.378228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.444862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.572361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.803444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.890173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.019948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.284827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.432394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.576365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.840716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.959362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.048122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.157957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.457062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.522757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.655716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.886449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:15.967129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.101801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.369472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.514838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.659027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:21.924154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.039388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.126312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.237235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:26.539985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:12.604616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:13.829267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:14.970265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:16.049294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:17.188884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:18.455072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:19.602053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:20.746164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:22.010368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:23.122792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:24.206861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:25.321012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-08T17:28:30.154098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Power (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
Power (kW)1.0000.0640.056-0.1050.6220.9920.992-0.1880.8850.6180.9750.833-0.130
Wind direction (°)0.0641.0000.9240.0300.0190.0630.063-0.1030.0490.0330.0700.0560.020
Nacelle position (°)0.0560.9241.0000.0360.0080.0540.054-0.1080.0400.0240.0610.0460.014
blade_angle-0.1050.0300.0361.000-0.463-0.118-0.1180.075-0.2360.037-0.0700.037-0.069
Rear bearing temperature (°C)0.6220.0190.008-0.4631.0000.6180.6120.0990.7880.3380.6000.4430.027
Rotor speed (RPM)0.9920.0630.054-0.1180.6181.0000.999-0.1820.8850.6140.9670.828-0.124
Generator RPM (RPM)0.9920.0630.054-0.1180.6120.9991.000-0.1950.8840.6140.9670.828-0.129
Nacelle ambient temperature (°C)-0.188-0.103-0.1080.0750.099-0.182-0.1951.000-0.131-0.123-0.188-0.1570.171
Front bearing temperature (°C)0.8850.0490.040-0.2360.7880.8850.884-0.1311.0000.5170.8610.708-0.083
Tower Acceleration X (mm/ss)0.6180.0330.0240.0370.3380.6140.614-0.1230.5171.0000.5760.848-0.094
Wind speed (m/s)0.9750.0700.061-0.0700.6000.9670.967-0.1880.8610.5761.0000.812-0.112
Tower Acceleration y (mm/ss)0.8330.0560.0460.0370.4430.8280.828-0.1570.7080.8480.8121.000-0.122
Metal particle count counter-0.1300.0200.014-0.0690.027-0.124-0.1290.171-0.083-0.094-0.112-0.1221.000

Missing values

2023-07-08T17:28:26.658117image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-08T17:28:26.857207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-08T17:28:27.086229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
02020-01-01 00:00:00150.984141116.83946297.1464160.04983165.3824998.4494121004.0898806.76250065.880001103.1257973.88729130.390030687.0
12020-01-01 00:10:00130.414782115.65936197.1464160.07983364.7124988.345387990.9312116.85000064.602500120.0446813.84894132.042564687.0
22020-01-01 00:20:00146.401656116.646515100.7482780.07499964.9174998.4970441009.4775756.86500064.74000088.8931874.04362532.799056687.0
32020-01-01 00:30:0084.296224111.157642109.2195430.50033163.9900008.208632976.3861776.80750063.137500103.5524183.33034236.129912687.0
42020-01-01 00:40:0094.994105116.678227109.2195430.52666463.5250008.289365985.7661016.70500062.03750080.9931223.38853626.667582687.0
52020-01-01 00:50:00262.992229127.755441110.9311510.00000065.4657899.4528421124.4830526.83157965.11579059.9324024.70628226.168612687.0
62020-01-01 01:00:00449.115810131.613819130.0731350.00000068.72500011.0821411317.0484606.83000069.63000045.3762435.90245520.280807687.0
72020-01-01 01:10:00456.427864134.693861130.0731350.00000070.50250111.1833981326.9007996.89000072.31500133.1583415.73871522.654048687.0
82020-01-01 01:20:00433.714243130.266474130.0731350.00000070.62499911.0491011311.9052106.89000072.70499940.2319705.80797218.623027687.0
92020-01-01 01:30:00343.683160137.579890130.0731350.00000070.46750010.3069731223.7771436.97000072.48500149.9869595.43698219.431780687.0
# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
526942020-12-31 22:20:00-1.436716309.311422313.36538789.99333217.0950000.01.8602761.53018.7275015.9419596.1564696.913332708.0
526952020-12-31 22:30:00-1.022186307.221017313.36538789.99333216.8925000.02.1742321.57518.6425015.3887296.0739137.410512708.0
526962020-12-31 22:40:00-1.977685300.484751313.36538789.99333216.7700000.01.8027481.59518.5325005.8506295.5781447.639680708.0
526972020-12-31 22:50:00-1.550351300.563581313.36538789.99333216.6700000.04.1275171.64018.3225006.8116175.2374005.112100708.0
526982020-12-31 23:00:00-1.348688303.049183313.36538789.99333216.4450000.02.2065601.70018.1950006.4671505.3445755.291028708.0
526992020-12-31 23:10:00-3.748371303.499764313.36538789.99333216.2200010.01.4544681.84018.0400004.3498835.1194444.464453708.0
527002020-12-31 23:20:00-2.761930304.460909313.36538789.99333216.1475010.01.4692071.79017.8399994.9218905.0096814.589267708.0
527012020-12-31 23:30:00-2.240700300.909886313.36538789.99333215.9850000.01.4343351.84017.7699994.5100905.0608134.916669708.0
527022020-12-31 23:40:00-4.011920297.398429313.36538789.99333215.8000000.01.4307161.88517.5600005.2894284.8142694.877768708.0
527032020-12-31 23:50:00-2.042772302.284452313.36538789.99333215.7350000.01.4509591.72017.4500005.1735675.4774004.837099708.0